from aimodel import embedding_model

import faiss
from langchain_community.vectorstores import FAISS
from langchain_community.docstore.in_memory import InMemoryDocstore

index1 = faiss.IndexFlatL2(len(embedding_model.embed_query("world")))
index2 = faiss.IndexFlatL2(len(embedding_model.embed_query("hello")))

faiss_embedding1 = FAISS(
    embedding_function=embedding_model,
    index=index1,
    docstore= InMemoryDocstore(),
    index_to_docstore_id={}
)

faiss_embedding2 = FAISS(
    embedding_function=embedding_model,
    index=index2,
    docstore= InMemoryDocstore(),
    index_to_docstore_id={}
)